As integrated circuit (IC) feature sizes shrink into the sub-wavelength regime, improved photolithography resolution increases frequency of yield impacting repeating defects from mask defects and resolution enhancements techniques (RET). Therefore, process window qualification (PWQ) to qualify a mask includes both mask inspection before wafer printing and wafer inspection after wafer printing.
Semiconductor device design and reticle manufacturing quality are verified by different procedures before the reticle enters a semiconductor fabrication facility to begin production of integrated circuits. The semiconductor device design is checked by software simulation to verify that all features print correctly after lithography in manufacturing. The reticle is inspected at the mask shop for reticle defects and measured to ensure that the features are within specification. Marginal RET designs not noted by simulation checks translate into electrical failures in wafer fabrication, affect yield, and possibly remain unnoticed until wafer fabrication is complete.
PWQ is a type of inspection performed on a specimen fabricated in a particular way that can check if a specific chip design can be manufactured (e.g., free of critical hot spots) and to decide about the optimal parameters for a lithography process (e.g., focus/exposure). Usually, a focus-exposure modulated specimen is printed to simulate different process window conditions. The specimen is then inspected using a relatively sensitive bright field (BF) inspection tool. The detected defects are divided into bins by a design-based algorithm that classifies the defects by type of printing error (a unique design structure is associated with each bin). To determine how a printing error is affecting the chip yield at different process modulations, a defect sampling strategy followed by scanning electron microscope (SEM) review is performed. For example, a few representative defects from each bin can be visited at different die modulations. This time-consuming procedure checks how a structure responds to changes in lithography parameters (focus/exposure) and finally the process window limits are determined. To increase sensitivity, a second iteration is sometimes performed. In that case, the previously identified printing errors can be used as care areas in the wafer inspection. The complete procedure may then be repeated.
The nature of PWQ is to induce pattern anomalies, such as transient repeating defects, by varying a process parameter or operating variable, such as focus, exposure, partial coherence of illumination, mode of illumination, or numerical aperture. Transient or “soft” repeating defects are defects that print under only specific conditions, such as, for example, defocus level, exposure dose, and photoresist uniformity conditions. The term “soft defects” also refers to defects that are cleanable, unlike “hard defects,” in which the pattern is permanently cast in the reticle. The narrowing process window, which is primarily reduced depth of focus, is used to intentionally amplify any unexpected patterning behavior. The method increases the capture rate of pattern anomalies that sometimes depend on coincidental confluence of exposure, focus, illumination, and resolution enhancement technology patterning at the wafer plane.
The PWQ procedure can implement die-to-die inspection of a plurality of dies or other repetitive patterns on a semiconductor wafer or other substrate on which design patterns are printed by photoresist patterning performed in accordance with a lithographic process using either a single die reticle or a multi-die reticle. The procedure entails selecting an illumination operating variable to modulate. A layer of pattern recording material such as a photoresist covering a test wafer substrate is exposed in the form of a grid of regions arranged in rows and columns. The columns are arranged in a pattern of “A” columns representing regions exposed to different values of a predetermined operating variable and “B” columns representing regions exposed to a common reference value of the predetermined operating variable. Conventional inspection techniques identifying differences in the “A” regions compared with the “B” regions eliminate hard repetitive anomalies. Comparing differences between “A” region values for a given column relative to a reference value identifies transient repetitive anomalies. Each repetitive anomaly identified is evaluated for critical status. The procedure of comparing images formed by different values of a lithographic operating variable enables qualifying single die reticles and detecting design pattern defects. If the anomaly identified is of a design pattern type, critical status would depend on the number of occurrences and location of the anomaly on the design pattern.
The process or yield criticality information may include, for example, critical defects determined by PWQ, locations of defects of interest (DOI) based on hot spots (e.g., determined from inspection), hot spot information determined from logical bitmaps, a kill probability (KP) value determined from test results for a defect detected at a hot spot, any other process or yield information, or some combination thereof. A “hot spot” may be generally defined as a location in the design printed on the wafer at which a killer defect may be present. In contrast, a “cold spot” may be generally defined as a location in the design printed on the wafer at which a nuisance defect may be present. Data for the one or more attributes of the die image may also be referred to as “context” data that defines geometrical areas in the die image that have different values of one or more attributes. For example, this may include type(s) of features within the areas such as contact areas or dummy fill areas, “where to inspect” information or “care areas,” “critical” areas in which a process failure is possible, or some combination thereof. The term context data is used interchangeably herein with the terms “context information” and “context map.” The context information may be acquired from a variety of sources including simulation, modeling, and/or analysis software products that are commercially available from KLA-Tencor, other software such as design rule checking (DRC) software, or some combination thereof.
PWQ leverages the unique ability of lithography tools to modulate lithography exposure process parameters at the reticle shot level using focus and exposure as variables to determine design-lithography interactions. This application is often used for optical proximity correction (OPC) verification. However, PWQ is limited to the direct comparison of dies on a wafer that are printed with modulated focus and/or exposure parameters. The impact of other process variables associated with process steps such as etch, deposition, thermal processing, chemical-mechanical polishing (CMP), etc. cannot be directly assessed by PWQ since these variables can only be modulated at the wafer level.
PWQ sampling has been based on the qualitative assessment of an expert, such as an applications engineer, who would set up PWQ inspection recipe and would use a host of sampling mechanisms. These mechanisms include design based grouping (DBG) based sampling and process condition based sampling.
With DBG-based sampling, defect patterns based on an exact match are grouped into bins and the bins are prioritized based on the frequency of failing patterns. The bin with highest population is ranked highest. This method of sampling is based on design processing, but not design understanding. DBG-based sampling ignores criticality of patterns and sampling is done based on design based grouping ranks, which is population dependent.
With process condition based sampling for PWQ, the wafer map is laid out in a way that each die is uniquely modulated by focus or exposure. From each die, a few defects are sampled based on defect attributes generated by a broad band plasma (BBP) inspection tool. The design based attributes of process condition based sampling and diversity sampling do not consider design attributes. It has often been observed that high signal is detected from regions where there are no patterns in the immediate vicinity or are non-critical from process window (PW) perspective. Often these defects are referred to as an SEM non visuals (SNV). The signal could be coming from a layer below and may have no relevance to the layer being inspected. Thus, the SEM review may not find anything at that location.
Therefore, improved techniques for performing PWQ are needed.